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What are grammars good for? Reflections on twenty years of Grammatical Framework

Chapter in book
Authors Aarne Ranta
Published in Tokens of Meaning: Papers in Honor of Lauri Karttunen
Pages 543-566
ISBN 1-68400-048-3
Publisher CSLI Publications
Place of publication Stanford
Publication year 2019
Published at Department of Computer Science and Engineering (GU)
Pages 543-566
Language en
Keywords grammar formalism, Grammatical Framework, syntactic analysis
Subject categories Computational linguistics


Grammars define concepts that make it possible to talk about language in a precise way. As demonstrated by finite state morphology, grammatical language processing can scale up to practical applications. Grammars can also be useful for statistical processing, since they provide abstractions that help with sparse data. In this paper, we investigate the use of grammars in syntactic analysis and machine translation. We do it by tracing the development of GF (Grammatical Framework), a grammar formalism that was first released in 1998 at Xerox Research Centre Europe in Grenoble and later became a collaborative open source project. The original use case for GF was sublanguage translation based on semantic interlinguas, but GF has later scaled up to wide coverage parsing and translation as well. Much of this is due to design decisions similar to the Xerox Finite State Tool: that grammars should be seen as transducers rather than classifiers; that one should be able to compose grammars that address different levels of analysis; that a grammar formalism should be mathematically clean and simple; and that its implementation should have separate source and run-time formats, where the source format is nice to work with and the run-time format is efficient to process.

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